The Coral M.2 Accelerator with Dual Edge TPU integrates two Edge TPUs into existing computer systems with the help of an M.2 E-key interface.
This Edge TPU module is particularly suitable for mobile and embedded systems that can benefit from accelerated machine learning.
Each Edge TPU coprocessor is capable of 4 billion arithmetic operations per second (4 TOPS) with 2-watt power consumption. For example, modern Mobile Vision models such as MobileNet v2 can run efficiently at close to 400 FPS.
With two Edge TPUs (and thus 8 TOPS) you can double the performance of the system - for example, by running two models in parallel, or by distributing the processing steps of a model between both Edge TPUs.
The M.2 Accelerator with Dual Edge TPU is supported under Debian Linux based systems as well as under Windows 10.
Interface: M.2 E-key (with two PCIe Gen2 x1 lanes)
Supports Linux, and Windows 10 on the host system
Other data
Dimensions: 22 mm x 30 mm x 2.8 mm (M.2-2230-D3-E)
Weight: 2.5 g
Operating temperature: -40 to + 85 ° C
Requirements for the host system
Linux:
64-bit Linux Debian 10.0 / Ubuntu 16.04 (or newer)
CPU architecture: x86-64, or ARMv8 (64-bit)
or Windows:
Windows 10 (64-bit),
x86-64 CPU architecture
Google Part Number
G650-06076-01
Important Notes
Although the M.2 specification requires that E-key sockets provide two PCIe x1 lanes, most manufacturers only provide PCIe once! In order to be able to use both Edge TPUs, please make sure that your socket actually provides two PCIe x1.
Please also note the information in the datasheet on peak current requirements (up to 3 A per EdgeTPU) and thermal management. Each Edge TPU contains a built-in temperature sensor and allows parameters to be configured when it should be switched off.
Warning: Overheating of the system can lead to fire or the destruction of hardware!
Potential for Industrial Applications
The Coral Edge TPU is a revolutionary product for machine learning applications. This enables embedded solutions that can, for example, recognize problems with workpieces, recognize traffic situations and much more.
Skip to content
